Abstract #4700

Diffusion-weighted MR Image Reconstruction using Automated Transform by Manifold Approximation (AUTOMAP) on Human Brains

Neha Koonjoo^1,2,3, Bo Zhu^1,2,3, Matthew Christensen^1,2, John E. Kirsch^1,2, Bragi Sveinsson^1,2,3, and Matthew S Rosen^1,2,3

¹A.A Martinos Biomedical Imaging Center / MGH, Charlestown, MA, United States, ²Harvard Medical School, Boston, MA, United States, ³Department of Physics, Harvard University, Cambridge, MA, United States

Low intrinsic Signal-to-Noise Ratio (SNR) in diffusion-weighted (DW) images are recurrent issues especially at high b-values. Here, we apply the deep neural network image reconstruction technique, AUTOMAP (Automated Transform by Manifold Approximation) to in-vivo diffusion-weighted MR data acquired at 1.5 T with varying b-values. In addition, apparent diffusion coefficient (ADC) maps were assessed. We also compared the reconstruction of the images using two different training corpura. The results for AUTOMAP reconstruction showed a significant increase in SNR.

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